Decision-Making

Survey report: What 1,000 business and data leaders think about using generative AI for analytics.

Persuading employees to use data to make better decisions requires both top-down leadership and grassroots initiatives.

Leaders who explore, evaluate, and refine their values set themselves up to make better decisions.

These tips can help leaders develop their own and employees’ ability to apply ethical judgment in difficult situations.

Leaders’ delegation decisions should reflect the trust they have in both their people and organizational processes.

This issue of MIT SMR focuses on sustainability, customer and employee engagement, and strategic planning.

A data monetization matrix can help leaders assess opportunities and approaches for converting data into revenue.

Simple rules of thumb can result in more effective decision-making than comprehensive analysis.

Black hat workshops can help you model your company’s competitive landscape before making the next strategic move.

Companies benefit when employees across demographics have an equal opportunity to affect organizational decision-making.

Agility can lead to negative outcomes if leaders don’t recognize the pitfalls in its processes.

UC Berkeley’s Ziad Obermeyer discusses how machine learning and AI are being used for medical research and diagnoses.

Not defining a problem well is one of the biggest obstacles to good decisions; use this simple story structure to help.

Decisions that have moral consequences often require sustained and systematic consideration.

Mentors can help redefine the rhetoric of success that rewards work at the cost of well-being.

Orangetheory Fitness members get the most out of their group workouts with some help from both AI and human coaches.

This issue of MIT SMR focuses on customer relationships and their connection to innovation and value.

Repeating false claims increases their believability, leaving business leaders vulnerable to faulty decision-making.

Categorizing decisions by riskiness and urgency helps clarify when to involve higher-ups.

When we rely on machines to make decisions, we substitute data-driven calculations for human judgment.